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This paper investigates flow and combustion in a full-cycle simulation of a four-stroke, three-valve HCCI engine by visualizing the flow with pathlines. Pathlines trace massless particles in a transient flow field. In addition to visualization, pathlines are used here to trace the history, or evolution, of flow fields and species. In this study evolution is followed from the intake port through combustion. Pathline analysis follows packets of intake charge in time and space from induction through combustion. The local scalar fields traversed by the individual packets in terms of velocity magnitude, turbulence, species concentration and temperatures are extracted from the simulation results. The results show how the intake event establishes local chemical and thermal environments in-cylinder and how the species respond (chemically react) to the local field.

The purpose of this research is to develop a prediction technique that can be used in the development of port fuel-injection (hereinafter called PFI) gasoline engines, especially for general purpose small utility engines. Utility engines have two contradictory desirable aspects: compactness and high-power at wide open throttle. Therefore, applying the port fuel injector to utility engines presents a unique intractableness that is different from application to automobiles or motorcycles. At the condition of wide open throttle, a large amount of fuel is required to output high power, and injected fuel is deposited as a wall film on the intake port wall. Despite the fuel rich condition, emissions are required to be kept under a certain level. Thus, it is significant to understand the wall film phenomenon and control film thickness in the intake ports.

In this paper, knock in a Ford single cylinder direct-injection spark-ignition (DISI) engine was modeled and investigated using the KIVA-3V code with a G-equation combustion model coupled with detailed chemical kinetics. The deflagrative turbulent flame propagation was described by the G-equation combustion model. A 22-species, 42-reaction iso-octane (iC8H18) mechanism was adopted to model the auto-ignition process of the gasoline/air/residual-gas mixture ahead of the flame front. The iso-octane mechanism was originally validated by ignition delay tests in a rapid compression machine. In this study, the mechanism was tested by comparing the simulated ignition delay time in a constant volume mesh with the values measured in a shock tube under different initial temperature, pressure and equivalence ratio conditions, and acceptable agreements were obtained.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

The lift-off length plays a significant role in spray combustion as it influences the air entrainment upstream of the lift-off location and hence the soot formation. Accurate prediction of lift-off length thus becomes a prerequisite for accurate soot prediction in lifted flames. In the present study, KIVA-3v coupled with CHEMKIN, as developed at the Engine Research Center (ERC), is used as the CFD model. Experimental data from the Sandia National Labs. is used for validating the model predictions of n-heptane lift-off lengths and soot formation details in a constant volume combustion chamber. It is seen that the model predictions, in terms of lift-off length and soot mass, agree well with the experimental results for low ambient density (14.8 kg/m3) cases with different EGR rates (21% O2 - 8% O2). However, for high density cases (30 kg/m3) with different EGR rates (15% O2 - 8% O2) disagreements were found.

Multi-zone CFD simulations with detailed kinetics were used to model iso-octane HCCI experiments performed on a single-cylinder research engine. The modeling goals were to validate the method (multi-zone combustion modeling) and the reaction mechanism (LLNL 857 species iso-octane) by comparing model results to detailed exhaust speciation data, which was obtained with gas chromatography. The model is compared to experiments run at 1200 RPM and 1.35 bar boost pressure over an equivalence ratio range from 0.08 to 0.28. Fuel was introduced far upstream to ensure fuel and air homogeneity prior to entering the 13.8:1 compression ratio, shallow-bowl combustion chamber of this 4-stroke engine. The CFD grid incorporated a very detailed representation of the crevices, including the top-land ring crevice and head-gasket crevice. The ring crevice is resolved all the way into the ring pocket volume. The detailed grid was required to capture regions where emission species are formed and retained.

Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

Predictive models of soot formation during Diesel combustion are of great practical interest, particularly in light of newly proposed strict regulations on particulate emissions. A modified version of the phenomenological model of soot formation developed previously has been implemented in KIVA-II CFD code. The model includes major generic processes involved in soot formation during combustion, i.e., formation of soot precursors, formation of surface growth species, soot particle nucleation, coagulation, surface growth and oxidation. The formulation of the model within the KIVA-II is fully coupled with the mass and energy balances in the system. The model performance has been tested by comparison with the results of optical in-cylinder soot measurements in a single cylinder Cummins NH Diesel engine. The predicted soot volume fraction, number density and particle size agree reasonably well with the experimental data.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.

Neural networks have been used for engine computations in the recent past. One reason for using neural networks is to capture the accuracy of multi-dimensional CFD calculations or experimental data while saving computational time, so that system simulations can be performed within a reasonable time frame. This paper describes three methods to improve upon neural network predictions. Improvement is demonstrated for in-cylinder pressure predictions in particular. The first method incorporates a physical combustion model within the transfer function of the neural network, so that the network predictions incorporate physical relationships as well as mathematical models to fit the data. The second method shows how partitioning the data into different regimes based on different physical processes, and training different networks for different regimes, improves the accuracy of predictions.

We have developed a methodology for predicting combustion and emissions in a Homogeneous Charge Compression Ignition (HCCI) Engine. This methodology combines a detailed fluid mechanics code with a detailed chemical kinetics code. Instead of directly linking the two codes, which would require an extremely long computational time, the methodology consists of first running the fluid mechanics code to obtain temperature profiles as a function of time. These temperature profiles are then used as input to a multi-zone chemical kinetics code. The advantage of this procedure is that a small number of zones (10) is enough to obtain accurate results. This procedure achieves the benefits of linking the fluid mechanics and the chemical kinetics codes with a great reduction in the computational effort, to a level that can be handled with current computers.

An engine cycle simulation code with detailed chemical kinetics has been developed to study Homogeneous Charge Compression Ignition (HCCI) combustion with hydrogen as the fuel. In order to attain adequate combustion duration, resulting from the self-accelerating nature of the chemical reaction, fuel and temperature inhomogeneities have been brought to the calculation by considering the combustion chamber to have various temperature and fuel distributions. Calculations have been done under various conditions including both perfectly homogeneous and inhomogeneous cases, changing the degree of inhomogeneity. The results show that intake gas temperature is more dominant on ignition timing of HCCI than equivalence ratio and that there is a possibility to control HCCI by introducing appropriate temperature inhomogeneity to in-cylinder mixture.

The present study investigated HCCI combustion in a heavy-duty diesel engine both experimentally and numerically. The engine was equipped with a hollow-cone pressure-swirl injector using gasoline direct injection. Characteristics of HCCI combustion were obtained by very early injection with a heated intake charge. Experimental results showed an increase in NOx emission and a decrease in UHC as the injection timing was retarded. It was also found that optimization can be achieved by controlling the intake temperature together with the start-of-injection timing. The experiments were modeled by using an engine CFD code with detailed chemistry. The CHEMKIN code was implemented into KIVA-3V such that the chemistry and flow solutions were coupled. The model predicted ignition timing, cylinder pressure, and heat release rates reasonably well. The NOx emissions were found to increase as the injection timing was retarded, in agreement with experimental results.

We have developed a methodology for predicting combustion and emissions in a Homogeneous Charge Compression Ignition (HCCI) Engine. The methodology judiciously uses a fluid mechanics code followed by a chemical kinetics code to achieve great reduction in the computational requirements; to a level that can be handled with current computers. In previous papers, our sequential, multi-zone methodology has been applied to HCCI combustion of short-chain hydrocarbons (natural gas and propane). Applying the same procedure to long-chain hydrocarbons (iso-octane) results in unacceptably long computational time. In this paper, we show how the computational time can be made acceptable by developing a segregated solver. This reduces the run time of a ten-zone problem by an order of magnitude and thus makes it much more practical to make combustion studies of long-chain hydrocarbons.

A direct injection-gasoline (DI-G) system was applied to a heavy-duty diesel-type engine to study the effects of charge stratification on the performance of premixed compression ignited combustion. The effects of the fuel injection parameters on combustion phasing were of primary interest. The simultaneous effects of the fuel stratification on Unburned Hydrocarbon (UHC), Oxides of Nitrogen (NOx), Carbon Monoxide (CO), and smoke emissions were also measured. Engine tests were conducted with altered injection parameters covering the entire load range of normally aspirated Homogeneous Charge Compression Ignited (HCCI) combustion. Combustion phasing tests were also conducted at several engine speeds to evaluate its effects on a fuel stratification strategy.

A multi-zone model has been developed that accurately predicts HCCI combustion and emissions. The multi-zone methodology is based on the observation that turbulence does not play a direct role on HCCI combustion. Instead, chemical kinetics dominates the process, with hotter zones reacting first, and then colder zones reacting in rapid succession. Here, the multi-zone model has been applied to analyze the effect of piston crevice geometry on HCCI combustion and emissions. Three different pistons of varying crevice size were analyzed. Crevice sizes were 0.26, 1.3 and 2.1 mm, while a constant compression ratio was maintained (17:1). The results show that the multi-zone model can predict pressure traces and heat release rates with good accuracy. Combustion efficiency is also predicted with good accuracy for all cases, with a maximum difference of 5% between experimental and numerical results.

Diesel engine in-cylinder combustion processes have been studied using computational models with particular attention to spray development, vaporization, fuel/air mixture formation and combustion. A thermodynamic zero-dimensional cycle analysis program was used to determine initial conditions for the multidimensional calculations. A modified version of the time-dependent, three-dimensional computational fluid dynamics code KIVA-II was used for the computations, with a detailed treatment for the spray calculations and a simplified model for combustion. The calculations were used to obtain an understanding of the potential predictive capabilities of the models. It was found that there is a strong sensitivity of the results to numerical grid resolution. With proper grid resolution, the calculations were found to reproduce experimental data for non- vaporizing and vaporizing sprays. However, for vaporizing sprays with combustion, extremely fine grids are needed.

The simulation of combustion chemistry in internal combustion engines is challenging due to the need to include detailed reaction mechanisms to describe the engine physics. Computational times needed for coupling full chemistry to CFD simulations are still too computationally demanding, even when distributed computer systems are exploited. For these reasons the present paper proposes a time scale separation approach for the integration of the chemistry differential equations and applies it in an engine CFD code. The time scale separation is achieved through the estimation of a characteristic time for each of the species and the introduction of a sampling timestep, wherein the chemistry is subcycled during the overall integration. This allows explicit integration of the system to be carried out, and the step size is governed by tolerance requirements.

Due to concerns regarding pollutant and CO2 emissions, advanced combustion modes that can simultaneously reduce exhaust emissions and improve thermal efficiency have been widely investigated. The main characteristic of the new combustion strategies, such as HCCI and LTC, is that the formation of a homogenous mixture or a controllable stratified mixture is required prior to ignition. The major issue with these approaches is the lack of a direct method for the control of ignition timing and combustion rate, which can be only indirectly controlled using high EGR rates and/or lean mixtures. Homogeneous Charge Progressive Combustion (HCPC) is based on the split-cycle principle. Intake and compression phases are performed in a reciprocating external compressor, which drives the air into the combustor cylinder during the combustion process, through a transfer duct. A transfer valve is positioned between the compressor cylinder and the transfer duct.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.